Class LogisticRegressionSummaryImpl
Object
org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
- All Implemented Interfaces:
Serializable,ClassificationSummary,LogisticRegressionSummary,Summary
- Direct Known Subclasses:
BinaryLogisticRegressionSummaryImpl,LogisticRegressionTrainingSummaryImpl
Multiclass logistic regression results for a given model.
param: predictions dataframe output by the model's transform method.
param: probabilityCol field in "predictions" which gives the probability of
each class as a vector.
param: predictionCol field in "predictions" which gives the prediction for a data instance as a
double.
param: labelCol field in "predictions" which gives the true label of each instance.
param: featuresCol field in "predictions" which gives the features of each instance as a vector.
param: weightCol field in "predictions" which gives the weight of each instance.
- See Also:
-
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionField in "predictions" which gives the features of each instance as a vector.labelCol()Field in "predictions" which gives the true label of each instance (if available).Field in "predictions" which gives the prediction of each class.Dataframe output by the model'stransformmethod.Field in "predictions" which gives the probability of each class as a vector.Field in "predictions" which gives the weight of each instance.Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.classification.ClassificationSummary
accuracy, falsePositiveRateByLabel, fMeasureByLabel, fMeasureByLabel, labels, precisionByLabel, recallByLabel, truePositiveRateByLabel, weightedFalsePositiveRate, weightedFMeasure, weightedFMeasure, weightedPrecision, weightedRecall, weightedTruePositiveRateMethods inherited from interface org.apache.spark.ml.classification.LogisticRegressionSummary
asBinary
-
Constructor Details
-
LogisticRegressionSummaryImpl
-
-
Method Details
-
featuresCol
Description copied from interface:LogisticRegressionSummaryField in "predictions" which gives the features of each instance as a vector.- Specified by:
featuresColin interfaceLogisticRegressionSummary
-
labelCol
Description copied from interface:ClassificationSummaryField in "predictions" which gives the true label of each instance (if available).- Specified by:
labelColin interfaceClassificationSummary
-
predictionCol
Description copied from interface:ClassificationSummaryField in "predictions" which gives the prediction of each class.- Specified by:
predictionColin interfaceClassificationSummary
-
predictions
Description copied from interface:ClassificationSummaryDataframe output by the model'stransformmethod.- Specified by:
predictionsin interfaceClassificationSummary- Returns:
- (undocumented)
-
probabilityCol
Description copied from interface:LogisticRegressionSummaryField in "predictions" which gives the probability of each class as a vector.- Specified by:
probabilityColin interfaceLogisticRegressionSummary
-
weightCol
Description copied from interface:ClassificationSummaryField in "predictions" which gives the weight of each instance.- Specified by:
weightColin interfaceClassificationSummary
-